Systems and methods for fetal monitoring

ABSTRACT

A system obtains a maternal electrocardiogram (ECG) signal that represents an ECG of a pregnant mother during a first time interval. The system further obtains a mixed maternal-fetal ECG signal that represents a combined ECG of the mother and her fetus during the first time interval; processes the maternal ECG signal and the mixed maternal-fetal ECG signal to generate a fetal ECG signal that represents the ECG of the fetus during the time interval, the fetal ECG signal substantially excluding the maternal ECG signal; and provides an output based on the fetal ECG signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a National Stage application under 35 U.S.C. § 371of International Application No. PCT/US2018/019360, having anInternational Filing Date of Feb. 23, 2018, which claims the benefit ofU.S. Provisional Ser. No. 62/464,783 filed Feb. 28, 2017. The disclosureof the prior applications are considered part of (and are incorporatedby reference in) the disclosure of this application.

BACKGROUND

More than 350,000 babies are born every day, many in developingcountries where 45% of infant deaths occur in the neonatal stage. Of 2.6million stillbirths a year worldwide, 98% occur in developing countries.The United Nations has declared reducing child mortality as one of itsmillennium goals and in its 2016 fact sheet states: “Up to two thirds ofnewborn deaths could be prevented if skilled health workers performeffective health measures at birth and during the first week of life . .. ” Research has shown a strong connection between intrapartum stillbirth, neonatal death, infant morbidity and lack of fetal heartmonitoring in the United States and in developing nations. In the UnitedStates, fetal heart monitoring has been widely adopted and is used in86% of deliveries. Typical fetal heart-rate monitoring uses ultrasoundtechnology and can require considerable expertise for use. For example,motion can result in artifacts, signal dropout, and inadvertentacquisition of the maternal rather than fetal heart rate.

SUMMARY

This specification describes systems, methods, devices, and othertechniques for fetal monitoring.

Some aspects of the disclosed subject matter include a vaginal probe forsensing information about a patient from within a vaginal canal. Theprobe may include a ring-shaped body, one or more sets of sensors, awireless communications interface or a wired communications interface,and a controller. Shapes and form factors other than a “ring” may alsobe implemented, such as a tampon, cylinder, or a cup-shaped device, anyof which can include a multi-sensor array. By way of example, thisspecification sometimes refers to a ring-shaped probe, but it should beunderstood that other form factors may also be suitable. In someimplementations, the set of sensors includes a set of ECG sensors thatinclude one or more electrodes disposed on the ring-shaped body andconfigured to capture an ECG signal that at least partially representsfetal cardiac activity. The wireless communications interface isconfigured to wirelessly transmit radio frequency (RF) signals thatencode information about a maternal ECG signal or a mixed maternal-fetalECG signal. The controller can be configured to activate or deactivatesignal acquisition from the one or more sets of sensors and to controlwireless transmission of data from the probe.

Other aspects of the disclosed subject matter include acomputer-implemented method. The method can include obtaining, by asystem of one or more computers, a maternal electrocardiogram (ECG)signal that represents an ECG of a pregnant mother during a first timeinterval; obtaining, by the system, a mixed maternal-fetal ECG signalthat represents a combined ECG of the mother and her fetus during thefirst time interval; processing, by the system, the maternal ECG signaland the mixed maternal-fetal ECG signal to generate a fetal ECG signalthat represents the ECG of the fetus during the time interval, the fetalECG signal substantially excluding the maternal ECG signal; andproviding, by the system, an output based on the fetal ECG signal.

Yet other aspects of the disclosed subject matter include acomputer-implemented method that includes receiving, by a system of oneor more computers, a first ECG signal, wherein the first ECG signal is(i) a mixed maternal-fetal ECG signal that represents a combined ECG ofa pregnant mother and her fetus or (ii) a fetal ECG signal thatrepresents an ECG of the fetus substantially to the exclusion of an ECGof the mother; processing, by the system, the first ECG signal todetermine values for one or more features of the first ECG signal;determining, based on the determined values for the one or more featuresof the first ECG signal, a condition of at least one of the mother orthe fetus; and providing, by the system, an output based on thedetermined condition of the at least one of the mother or the fetus.

In some implementations, a system is configured to monitor and analyze afetal heart rate pattern (e.g., decreases in heart rate or otherchanges) to identify/screen for a substance-dependent mother (e.g., amother who has consumed opioids), thereby allowing early intervention toprevent or mitigate occurrences of neonatal abstinence syndrome. Inanother aspect, the invention described herein can identify/screen foralcohol dependent mothers so early intervention can be implemented toprevent or mitigate Fetal Alcohol Syndrome.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention pertains. Although methods and materialssimilar or equivalent to those described herein can be used to practicethe invention, suitable methods and materials are described below. Allpublications, patent applications, patents, and other referencementioned herein are incorporated by reference in their entirety. Incase of conflict, the present specification, including definitions, willcontrol. In addition, the materials, methods, and examples areillustrative only and not intended to be limiting.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is an illustration of an example environment for fetalmonitoring.

FIG. 2 is a diagram of an example vaginal probe.

FIG. 3 is an illustration of an example placement of a vaginal probe inthe vaginal canal of a patient.

FIG. 4 depicts an example feedback filtering system that is configuredto process a maternal ECG signal and a mixed maternal-fetal ECG signalto extract a fetal ECG signal.

FIG. 5 depicts a set of ECG waveforms plotted over a common timeinterval.

FIG. 6 is a schematic illustration of a dual-sampling technique that asystem may employ on a mixed maternal-ECG signal to optimize the signalfor further processing.

FIG. 7 is a schematic illustration of an example convolutional neuralnetwork system configured to estimate a heart rate and distress level ofa fetus based on ECG signals.

FIG. 8 is a schematic illustration of an example recurrent neuralnetwork system configured to estimate a heart rate and distress level ofa fetus based on ECG signals.

FIG. 9 depicts a flowchart for an example process for generating a fetalECG signal from a maternal ECG signal and a mixed maternal-fetal ECGsignal.

FIG. 10 depicts a flowchart of an example process for processing aninput ECG signal of a mother to generate outputs representing fetalheart rate, fetal distress level, or both.

FIG. 11 depicts a flowchart of an example process for extracting andprocessing fetal ECG signals.

FIG. 12 shows an example of a computing device 1200 and a mobilecomputing device that may be applied to any of the computing systems anddevices discussed herein. In some implementations, these devices in FIG.12 may be configured to perform, in a system of one or more computers,the computer-implemented methods described herein.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features,objects, and advantages will be apparent from the description anddrawings, and from the claims.

DETAILED DESCRIPTION

This specification describes systems, methods, devices, and othertechniques for performing fetal monitoring. In some aspects, aring-shaped vaginal probe includes embedded electrodes to enablepreferential acquisition of fetal ECG signals as a result of its closeproximity to the fetus when inserted in the mother's vaginal canal. Insome aspects, computer-based processing techniques using vector signalprocessing and independent component analysis, coupled with thering-shaped vaginal probe, may facilitate robust, continuous, fetal HRmonitoring and analysis.

Conventionally, fetal monitors have relied upon skin-surface Doppler andultrasound technology to detect and record a fetus's heart rate overtime. A fetal ECG (e.g., a tracing of the electrical activity of thefetus's heart) is typically only available using scalp electrodesaffixed to the fetus's head after membrane rupture, and even this optionwill usually be unavailable when the fetus is in a breach presentation.Accordingly, the techniques described herein are intended to at leastpartially overcome these shortcomings of conventional fetal monitoring.For example, simultaneous maternal and fetal ECG monitoring may permitearly detection of fetal academia, potentially preventing cerebral palsycaused by hypoxemia at birth. Additionally, the ring-shaped vaginalprobe may permit acquisition of additional biomarkers such as anelectromyogram (EMG), temperature, and intra-vaginal fluidcharacteristics. In some implementations, the ring-shaped vaginal probemay facilitate home-based fetal monitoring for sustained periods of time(e.g., continuous monitoring). In some implementations, the vaginalprobe may be used for pregnancy planning purposes. For example,temperature sensors, EMG electrodes, or both, may be used to monitorchanges in conditions of the pubic region of a woman over time during amenstruation cycle. The woman may use such information to planintercourse for appropriate times, e.g., to either avoid pregnancy or toincrease the likelihood of conception.

Referring to FIG. 1, an example environment 100 for fetal monitoring isdepicted. The environment 100 includes a system 102, where the system102 includes one or more computers in one or more locations. The system102 includes one, two, three, or more data acquisition channels forobtaining sensor data representing signals detected by sets of sensors104 a-n coupled to a patient. In general, the patient will be describedherein as a pregnant mother, although in other instances the patient maynot be pregnant, e.g., a woman who is tracking her menstrual cycle toincrease or decrease the likelihood of becoming pregnant as a result ofintercourse. Each data acquisition channel of the system 102 obtainsdata from a different set of sensors 104 a-n. For example, a first setof sensors 104 a may be ECG sensors (e.g., electrodes) located on achest or abdominal region of the patient, e.g., skin-surface ECG sensorssuch as in an abdominal patch. A second set of sensors 104 b may be ECGsensors (e.g., electrodes) located on an inserted vaginal probe locatednearer the fetus. The system 102 may obtain ECG signals from each set ofsensors 104 a, 104 b, and may process both to determine a fetal ECGsignal. The system 102 can be configured to extract a fetal ECG signalfrom a mixed maternal-fetal ECG signal, and optionally, from a maternalECG signal that substantially excludes the fetal ECG signal. In someimplementations, the system 102 processes a mixed maternal-fetal ECGsignal obtained from vaginal ECG sensors alone (e.g., without signalsfrom abdominal or other skin-surface ECG sensors). In someimplementations, the system 102 processes a mixed maternal-fetal ECGsignal obtained from abdominal or other skin-surface ECG sensors alone(e.g., without signals from vaginal ECG sensors). In someimplementations, the system 102 processes a mixed maternal-fetal ECGsignal obtained from both vaginal ECG sensors and abdominal or otherskin-surface ECG sensors (e.g., using electrode(s) placed on thepatient's thigh as a reference). The latter, hybrid, approach may beuseful in some instances where a reference electrode is available. Awire to an extra-vaginal electrode may serve as an antenna for externalcommunication.

The system 102 may include all or some of components 106-118. Eachcomponent 106-118 may include a combination of software and hardwarethat are configured to perform the operations described herein.

The signal pre-processing subsystem 106 receives sensor data from thesets of sensors 104 a-n. If the received sensor data is in analog form,the subsystem 106 may use an analog-to-digital converter to sample anddigitize the sensor signals. The pre-processing subsystem 106 may alsoamplify and filter all or some of the signals from the sensors 104 a-nto prepare the signals for further processing. In some implementations,the pre-processing subsystem 106 synchronizes signals from differentsets of sensors 104 a-n. For instance, two channels of ECG sensor datamay be synchronized so that the beats shown in waveforms among each ofthe channels are aligned in the time dimension. In some instances,synchronization is performed by using a common clock or synchronizedclocks to timestamp frames of data from each sensor data that arereceived concurrently on each channel.

The fetal heart rate monitor subsystem 108 is configured to process atleast one of a fetal ECG signal or a mixed maternal-fetal ECG signal todetermine the heart rate of a fetus. The heart rate may be aninstantaneous or average heart rate over a window of time. In someimplementations, as described with respect to FIGS. 7, 8, and 10 below,the fetal heart rate monitor subsystem 108 uses a neural network system,e.g., including one or more convolutional or recurrent neural networks,to process the input ECG signal to determine the fetal heart rate. Othermachine-learning or predictive models may also be employed to processinput ECG signal(s) and to determine the fetal heart rate, such ascomputation of invariants such as multiscale contractions, linearizationof hierarchical symmetries, sparse separations, unsupervised clustering,or a combination of these and other techniques.

The fetal ECG monitor subsystem 110 is configured to determine a fetalECG signal from one or more input ECG signals. The input ECG signals caninclude a mixed maternal-fetal ECG signal and, optionally, a maternalECG signal that is substantially independent of the fetal ECG signal.The mixed maternal-fetal ECG signal may be obtained, for example, from aring-shaped vaginal probe having ECG electrodes therein that is insertedin the vaginal canal of the mother. Due to the close proximity to thefetus, the influence of the fetal ECG may be more pronounced on thesignal detected by the vaginal probe than if the ECG signal wereacquired by sensors affixed to the patient at other locations, such asan abdominal patch through use of a standard 12-lead ECG. The signaldetected by the electrodes on the vaginal probe may also besignificantly influenced by the mother's own cardiac electricalactivity. Thus, the signal detected by the vaginal probe may be a mix ofboth the maternal ECG signal and the fetal ECG signal.

In some implementations the fetal ECG monitor subsystem 110 includes afetal ECG analysis engine. The fetal ECG analysis engine processes afetal ECG signal and predicts likelihoods that the mother or fetus has,or is at risk of developing, one or more conditions based on features ofthe fetal ECG signal. For example, the fetal ECG analysis engine maydetermine a representative fetal beat waveform from the fetal ECG signalby excluding noisy beats from a set of beats over a timer interval andaveraging or otherwise combining the non-excluded beats. Alternatively,the representative fetal beat may be selected from the set of beatsbased on one or more criteria. The fetal ECG monitor subsystem 110determines values for one or more features of the beats. Examples offeatures of the representative beat are features of its waveform such asQ-T intervals, slope of the ascending portion of the T-wave, slope ofthe descending portion of the T-wave, maximum or average amplitude ofthe T-wave, area under the T-wave, or corresponding features for otherportions of the waveform such as the QRS complex. The feature values canthen be provided as input to a model, e.g., a statistical model, arules-based model, or an artificial neural network, to generate scoresthat represent the likelihoods of one or more maternal or fetalconditions occurring such as fetal academia, fetal pO₂, fetal pH, and/orfetal cardiac anomalies. The patient or a healthcare provider may bealerted if the likelihoods of certain conditions are sufficiently high.Other machine-learning or predictive models may also be suitable, suchas computation of invariants such as multiscale contractions,linearization of hierarchical symmetries, sparse separations,unsupervised clustering, or a combination of these and other techniques.

The menstrual cycle monitor subsystem 112 is configured to provideservices related to menstrual cycle tracking for a woman. The subsystem112 obtains data from one or more sources including data representing ahigh fidelity electromyogram (EMG) signal detected by EMGsensors/electrodes an inserted vaginal probe. The EMG sensors may beconfigured to contact the cervix in use to obtain high fidelity signals.In some implementations, the subsystem 112 also obtains and processestemperature signals sensed by one or more temperature sensors on thevaginal probe. Using the sensor data representing EMG signals,temperature signals, or both, the menstrual cycle monitor subsystem 112uses a personalized menstrual cycle model to precisely identify thetiming of when ovulation has occurred. The model may further be appliedto predict ovulation timing. Accordingly, the patient may be able toreduce or increase the probability of conceiving as a result ofintercourse.

The alert management and generation subsystem 114 is configured togenerate and present alerts to one or more users when a defined alertevent is detected to have occurred, or is predicted to occur. Forexample, the alert subsystem 114 may continuously monitor a fetal heartrate and distress level. If the heart rate or distress level becomes toohigh and exceeds a threshold heart rate or distress level (e.g., exceedsonce, multiple times, or for a minimum period of time), then an alertmay be generated. Alerts may be in any suitable form to grab users'attention such as audible, visual, or haptic feedback, or a combinationof these. In some implementations, the alert subsystem 114 generates amessage for a user in an external communication channel such as email,SMS messages, mobile alerts, or social media alerts. In someimplementations, the vaginal probe may include a vibration mechanismsuch as an off-balanced motor that provides vibratory feedback to thepatient when the probe is inserted in the vaginal canal in response todetecting certain events. For example, vaginal probe may be configuredto vibrate if the fetal heart rate or distress level exceeds athreshold. For menstrual cycle monitoring, the vaginal probe may vibrateto alert the woman to phases of the cycle, such as the beginning or endof fertility windows. Vibratory alerts can be beneficial to generatebrief vibration pulses in a private manner without the need for thepatient to read alerts from an external device.

In some implementations, the system 102 further includes a set of globalor personalized patient models 118 a-n. The patient models 118 a-n maybe used by the fetal heart rate monitor subsystem 108, the fetal ECGmonitor subsystem 110, or both to determine heart rate, distress levels,fetal ECG, or other outputs based on one or more input signals such as amaternal ECG signal and a mixed maternal-fetal ECG signal. In someimplementations, the patient models 118 a-n are binned based oncharacteristics of the mother, fetus, or both. For example, the system102 may select a different one of the models 118 a-n depending on theage and weight of the mother and based on the gestational age of thefetus.

FIG. 2 is a diagram of an example vaginal probe 200. The vaginal probe200 is configured to be inserted within the vaginal canal of a patientto permit monitoring of one or more conditions related to thereproductive areas of the patient and/or of a fetus of a pregnantpatient. In some implementations, the vaginal probe is an independent,optionally flexible, device that can be readily inserted by a patient(self-insertable) that records physiologic information about the patientand wirelessly transmits the physiologic information to an externaldevice such as a smartphone or dedicated reader. Although in someimplementations the vaginal probe may additionally or alternativelycontain a wire “tail” that physically connects the probe in use to anexternal device, in other implementations the vaginal probe isindependent and relies on wireless RF transmissions to communicate withan external device.

The vaginal probe 200 can include a collection of sensors 202 that areconfigured to produce signals indicating one or more conditions of thepatient (e.g., physiologic information) that are detectable from thevaginal canal. The sensors 202 can include one or more of ECGsensors/electrodes, EMG sensors/electrodes, pH sensors, ultrasoundsensors, ultrasound transmitter, temperature sensors, and sensors thatare configured to detect the presence of specific chemicals or fluids.The body of the probe may have a ring-like shape, e.g., made from ametallic alloy such as nitinol, that is structured and dimensioned to beinserted within the vaginal canal as depicted in FIG. 3, which shows anexample vaginal ring (probe) 302 inserted within the vaginal canal of apatient to allow for monitoring of various conditions from within thecanal. In some implementations, the vaginal probe may have a shape orform factor other than a “ring,” such as a tampon, cylinder, or acup-shaped device with multi-sensor array. By way of example, thisspecification generally refers to a ring-shaped probe, but it should beunderstood that other shapes or form factors may be suitable as well.The rings 200, 302 can include a controller 204 a, one or more sets ofsensors 202, a power source 204 c, and a wireless communicationsinterface 204 d. The wireless communications interface 204 d isconfigured to transmit RF signals encoded with informationcharacterizing sensor data to an external computing system, e.g., system102. In some implementations, the external computing system is orincludes a smartphone, a wearable device, a tablet, or another mobiledevice that allows the patient or the patient's healthcare provider toeasily receive data wirelessly transmitted from the vaginal probe. Insome implementations, the wireless interface 204 d is a BLUETOOTH® radioincluding a short-range radio transmitter and receiver, or is an IEEE802.11 WI-FI radio. The controller 204 a can be a microcontroller orother data processing apparatus configured to control, for example,parameters for how and when data from one or more of the sets of sensors202 is captured and transmitted to the external computing system.

The vaginal probe 200 can include a power supply 204 c, which may eitherbe an active power source such as a rechargeable battery, or a passivepower source. For implementations that provide a passive power source,the probe 200 may include one or more metallic coils that are configuredto generate electrical power based on induction from an inductive powersource external to the patient that is brought in proximity (e.g., lessthan about 2 inches, less than about 1 inch, less than about 0.5 inches,or less than about 0.25 inches) of the coil in the vaginal probe 200. Insome implementations, the controller 204 a of the probe 200 isconfigured to only activate signal acquisition/capture from the sensors202 and/or to cause the wireless interface 204 d to transmit sensor dataonly when the external, inductive power source is brought into proximityof the probe 200 when the probe 200 is located in the vaginal canal ofthe patient.

In some implementations, a computing system can obtain sensor data fromwhich a fetal ECG signal is determined. FIG. 9 depicts a flowchart foran example process 900 for generating a fetal ECG signal from a maternalECG signal and a mixed maternal-fetal ECG signal. The process 900 may becarried out, for example, by a fetal ECG monitor of a computing system,e.g., fetal ECG monitor subsystem 110 of system 102. At stage 902, thesystem obtains a maternal ECG signal that represents electrical activityof the heart of a pregnant mother. The ECG signal may show a repetitivewaveform, for example, in an electrical tracing that indicates theelectrical potential between particular lead vectors coupled to thepatient. The maternal ECG signal may be obtained, for example, from anabdominal or chest region of the patient and may be sufficiently distantfrom the fetus such that any influence of the fetal ECG may be deminimis. Optionally, at stage 904, the maternal ECG signal may befiltered, e.g., using a Wiener filter.

At stage 906, the system obtains a mixed maternal-fetal ECG signal. Themixed maternal-fetal ECG signal may be obtained, for example, from avaginal probe, e.g., probe 200, from within a vaginal canal of themother. The ECG electrodes on the probe 200 may be positioned near theuterus or other organ to be as close as feasible to the fetus in orderto permit capturing of signals resulting from the fetal heartbeat.Because the electrodes are still not directly coupled to the fetus, thecaptures ECG signal is a mixed maternal-fetal ECG signal. In someimplementations, the power contribution of the maternal ECG signal maybe much greater than the power contribution of the fetal ECG signal. Atstage 908, the mixed maternal-fetal ECG signal is optionally filtered byone or more digital filters.

At stage 910, the system processes the maternal ECG signal and the mixedmaternal-fetal ECG signal to isolate the fetal ECG signal. In someimplementations, the fetal ECG signal is obtained by subtracting thematernal ECG signal from the mixed maternal-ECG signal. In someimplementations, blind source separation, independent component analysis(ICA), principal component analysis (PCA), or a combination of these canbe performed to separate the fetal ECG signal using the pair of inputsignals, i.e., using the maternal ECG signal and the mixedmaternal-fetal ECG signal. Furthermore, in some implementations, thesystem may select a particular ECG vector for the maternal-fetal ECGand/or for the maternal ECG signal in order to optimize the ability toextract a high fidelity fetal ECG signal. An ECG vector refers to theECG signal that results from the electrical potential between aparticular pair of ECG leads/sensors. For example, a ring-shaped vaginalprobe may have 2, 4, 6, 8, 10, or 12 ECG leads in some implementations.The electrical potential as measured between each possible pair of leadsconstitutes an ECG vector. The system may select a particular pair ofleads and corresponding ECG vector to process in determining a fetal ECGsignal based on various criteria such as signal to noise ratio,positioning of the leads in the vaginal canal, spacing of the leads onthe probe, or a combination of these. For example, if the vaginal proberotates to some degree in use, or if the position of the fetus changesrelative to the location of the probe, the system may dynamicallyre-select leads and corresponding ECG vectors to obtain an optimal fetalECG as conditions change.

At stage 912, the system generates an output using the fetal ECG signal.For example, a tracing of the fetal ECG waveform may be displayed on amonitor for presentation to the patient or healthcare provider. FIG. 5depicts a set of ECG waveforms plotted over a window of time. A maternalECG signal is represented by plot 502, a mixed maternal-fetal ECG signalis represented by plot 504, and a fetal ECG signal that has beenextracted from the mixed maternal-fetal ECG signal is represented byplot 506.

FIG. 4 shows a feedback filtering system for extracting a fetal ECGsignal. The system provides a maternal ECG signal 402 to a filter 408,which outputs a filtered maternal ECG signal. The filtered maternal ECGsignal is then subtracted from a mixed maternal-fetal ECG signal 404 torecover the fetal ECG signal 406. In some implementations, the fetal ECGsignal 406 is used as feedback to an adaptive component of the filter408 to adjust parameters of the filter 408 based according to currentconditions of the fetal ECG signal 406.

FIG. 6 is a schematic illustration of a dual-sampling technique that asystem may employ on a mixed maternal-ECG signal to optimize the signalfor further processing. A mixed maternal-ECG signal 602 is sampledtwice, i.e., once by A/D converter 610 a and once by A/D converter 610b. The first A/D converter 610 a samples the signal 602 after it hasbeen amplified by amplifier 608. The amplified signal may extend outsidethe dynamic range of the A/D converter 610 a, thereby causing peaks inthe maternal ECG portion of the signal to be clipped. The signalcombiner 612 combines the signals from each A/D converter 610 a, 610 bto generate a higher resolution signal that what may otherwise have beensampled.

FIGS. 7 and 8 depict illustrate example neural network systems that aretrained to generate outputs representing a fetal heart rate based on aninput ECG signal and, optionally, auxiliary patient data. The input ECGsignal can be, for example, the fetal ECG signal or the mixedmaternal-fetal ECG signal. In some implementations, the neural networksystem is a convolutional neural network. FIG. 7 depicts an exampleconvolutional neural network 700. In other implementations, the neuralnetwork system is a recurrent neural network. FIG. 8 depicts an examplerecurrent neural network 800.

Neural networks are machine learning models that employ one or morelayers of nonlinear units to predict an output for a received input.Some neural networks include one or more hidden layers in addition to anoutput layer. The output of each hidden layer is used as input to thenext layer in the network, i.e., the next hidden layer or the outputlayer. Each layer of the network generates an output from a receivedinput in accordance with current values of a respective set ofparameters.

The neural networks may be global models or personalized model. Forglobal models, the network can be trained using a retrospective databaseof maternal and fetal ECG with fetal hear rate as the target output,where the fetal heart rate in the training data may have beenascertained in any suitable manner (e.g., directly using scalpelectrodes, CTG device). The model may also use auxiliary patient dataat training stage, such as the baby's pH level (e.g., a marker foracidimia), electrolytes from umbilical cord blood, oxygen level, cardiacanomalies, and others to predict fetal distress using the input ECGsignal. The global model can be a single model or multiple models basedon bins such as mother's weight, age, maternal heart rate in rest, or acombination of these and other factors. For personalized models, afterpositioning the ECG sensors on the mother, a training session isperformed to train the model specifically to the particular mother.

The recurrent neural network can be configured to continuously processneural network inputs representing the input ECG signal for a respectiveperiod of time. The convolutional neural network can be configured toreceive portions of the input ECG signal, where the windows representedby each portion may overlap. For both the recurrent and convolutionalnetwork implementations, the neural network system outputs informationindicating the fetal heart rate (e.g., 30-200 bpm) and the likelihood(e.g., probability) for fetal distress. In some implementations, thethresholds for determining when to generate an alert may be based onboth the fetal hear rate and predicted fetal distress.

FIG. 10 depicts a flowchart of an example process 1000 for processing aninput ECG signal of a mother to generate outputs representing fetalheart rate, fetal distress level, or both. In some implementations theprocess 1000 is performed using a neural network system such as therecurrent or convolutional neural network systems depicted in FIGS. 8and 9. The neural network system first obtains an input ECG signal,e.g., a mixed maternal-fetal ECG signal (1002). Optionally, the systemalso obtains auxiliary fetal distress data (auxiliary patient data)(1004). The system generates neural network inputs based on the mixedmaternal-fetal ECG signal and, optionally, auxiliary fetal distress data(1006). The neural network then processes the neural network inputs togenerate outputs representing fetal heart rate, and optionally, anindication of a fetal distress level (1008 and 1010). Having determinedthe heart rate and fetal distress level, the system may then processthese outputs in any suitable manner. In some implementations, thesystem generates an alert to notify a user of the occurrence of adetected problem or other pre-defined event, e.g., if the heart rate andfetal distress level are outside acceptable boundaries as indicated byone or more threshold values.

FIG. 11 depicts a flowchart of an example process 1100 for extractingand processing fetal ECG signals. In some implementations, the processis carried out by a system of one or more computers, e.g., system 102.At stage 1102, the system obtains a mixed maternal-fetal ECG signal and,optionally, a maternal ECG signal. At stage 1104, the system processesthe obtained ECG signal to derive a fetal ECG signal (stage 1104). Atstage 1106, the system identifies the maternal ECG signal thatcorresponds to the mixed signal for processing. At stage 1108, thesystem analyzes the fetal ECG signal to determine features of arepresentative beat in the fetal ECG signal. At stage 1110, the systemanalyzes the maternal ECG signal to determine features of arepresentative beat the maternal ECG signal. At stage 1112, the systemprocesses fetal ECG features and/or maternal ECG features to determinevalues indicative of one or more maternal and/or fetal conditions. Atstage 1114, the system generates alerts, reports, or other outputs basedon determined values that indicate likelihoods of one or more maternaland/or fetal conditions.

In some implementations, the systems described herein may be adapted toadditional or alternative aspects, including, for example, a system fordetecting physiologic changes in an infant or otherwise young individual(e.g., under 3, 6, 9, 12, 15, 18, 21, 24, or 36 months of age) iscontemplated, especially where the detected changes relate to symptomsof neonatal abstinence syndrome. The system may thus be utilized as ascreening tool for the syndrome. Neonatal abstinence syndrome generallyrefers to the withdrawal experienced by infants after birth, although inthis case it can also refer to the experience of fetuses in utero due tothe withdrawal of drugs of dependence from when they are abusedantenatally by the mother. The physiologic changes in association withdrug withdrawal depends on the specific drug withdrawn, but can includechanges in heart rate, respiratory rate, agitation, gastrointestinalchanges, convulsions, high-pitched cry, Moro reflex, tremors,irritability, altered sleep, or a combination of these. Elevatedtemperature, tachypnea, apnea, nasal congestion, nasal flaring, andyawning have also been described. According to the techniques here, thesystem can include one or more sensors configured to be worn or embeddedin a shirt, and that by means of artificial intelligence or other models(e.g., machine-learning models such as deep neural networks), canidentify the physiologic changes to suggest withdrawal from suchsubstances. For example, the system may monitor, via data obtained fromthe sensors, changes in maternal physiologic reporting including heartrate, electrocardiographic changes, repolarization, ST or QRS changes inassociation with simultaneous or temporally connected respiratory skinbioimpedance or mechanical changes, thereby permitting the system todetect (e.g., and thrown an alert/alarm when identified) presence orwithdrawal of drugs including methadone, heroin, amphetamine, alcohol,marijuana, LSD, caffeine or nicotine.

FIG. 12 shows an example of a computing device 1200 and a mobilecomputing device that can be used to implement the techniques describedherein. The computing device 1200 is intended to represent various formsof digital computers, such as laptops, desktops, workstations, personaldigital assistants, servers, blade servers, mainframes, and otherappropriate computers. The mobile computing device is intended torepresent various forms of mobile devices, such as personal digitalassistants, cellular telephones, smart-phones, and other similarcomputing devices. The components shown here, their connections andrelationships, and their functions, are meant to be exemplary only, andare not meant to limit implementations of the inventions describedand/or claimed in this document.

The computing device 1200 includes a processor 1202, a memory 1204, astorage device 1206, a high-speed interface 1208 connecting to thememory 1204 and multiple high-speed expansion ports 1210, and alow-speed interface 1212 connecting to a low-speed expansion port 1214and the storage device 1206. Each of the processor 1202, the memory1204, the storage device 1206, the high-speed interface 1208, thehigh-speed expansion ports 1210, and the low-speed interface 1212, areinterconnected using various busses, and may be mounted on a commonmotherboard or in other manners as appropriate. The processor 1202 canprocess instructions for execution within the computing device 1200,including instructions stored in the memory 1204 or on the storagedevice 1206 to display graphical information for a GUI on an externalinput/output device, such as a display 1216 coupled to the high-speedinterface 1208. In other implementations, multiple processors and/ormultiple buses may be used, as appropriate, along with multiple memoriesand types of memory. Also, multiple computing devices may be connected,with each device providing portions of the necessary operations (e.g.,as a server bank, a group of blade servers, or a multi-processorsystem).

The memory 1204 stores information within the computing device 1200. Insome implementations, the memory 1204 is a volatile memory unit orunits. In some implementations, the memory 1204 is a non-volatile memoryunit or units. The memory 1204 may also be another form ofcomputer-readable medium, such as a magnetic or optical disk.

The storage device 1206 is capable of providing mass storage for thecomputing device 1200. In some implementations, the storage device 1206may be or contain a computer-readable medium, such as a floppy diskdevice, a hard disk device, an optical disk device, or a tape device, aflash memory or other similar solid state memory device, or an array ofdevices, including devices in a storage area network or otherconfigurations. The computer program product may also containinstructions that, when executed, perform one or more methods, such asthose described above. The computer program product can also be tangiblyembodied in a computer- or machine-readable medium, such as the memory1204, the storage device 1206, or memory on the processor 1202.

The high-speed interface 1208 manages bandwidth-intensive operations forthe computing device 1200, while the low-speed interface 1212 manageslower bandwidth-intensive operations. Such allocation of functions isexemplary only. In some implementations, the high-speed interface 1208is coupled to the memory 1204, the display 1216 (e.g., through agraphics processor or accelerator), and to the high-speed expansionports 1210, which may accept various expansion cards (not shown). In theimplementation, the low-speed interface 1212 is coupled to the storagedevice 1206 and the low-speed expansion port 1214. The low-speedexpansion port 1214, which may include various communication ports(e.g., USB, Bluetooth, Ethernet, wireless Ethernet) may be coupled toone or more input/output devices, such as a keyboard, a pointing device,a scanner, or a networking device such as a switch or router, e.g.,through a network adapter.

The computing device 1200 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as astandard server 1220, or multiple times in a group of such servers. Inaddition, it may be implemented in a personal computer such as a laptopcomputer 1222. It may also be implemented as part of a rack serversystem 1224. Alternatively, components from the computing device 1200may be combined with other components in a mobile device (not shown),such as a mobile computing device 1250. Each of such devices may containone or more of the computing device 1200 and the mobile computing device1250, and an entire system may be made up of multiple computing devicescommunicating with each other.

The mobile computing device 1250 includes a processor 1252, a memory1264, an input/output device such as a display 1254, a communicationinterface 1266, and a transceiver 1268, among other components. Themobile computing device 1250 may also be provided with a storage device,such as a micro-drive or other device, to provide additional storage.Each of the processor 1252, the memory 1264, the display 1254, thecommunication interface 1266, and the transceiver 1268, areinterconnected using various buses, and several of the components may bemounted on a common motherboard or in other manners as appropriate.

The processor 1252 can execute instructions within the mobile computingdevice 1250, including instructions stored in the memory 1264. Theprocessor 1252 may be implemented as a chipset of chips that includeseparate and multiple analog and digital processors. The processor 1252may provide, for example, for coordination of the other components ofthe mobile computing device 1250, such as control of user interfaces,applications run by the mobile computing device 1250, and wirelesscommunication by the mobile computing device 1250.

The processor 1252 may communicate with a user through a controlinterface 1258 and a display interface 1256 coupled to the display 1254.The display 1254 may be, for example, a TFT (Thin-Film-Transistor LiquidCrystal Display) display or an OLED (Organic Light Emitting Diode)display, or other appropriate display technology. The display interface1256 may comprise appropriate circuitry for driving the display 1254 topresent graphical and other information to a user. The control interface1258 may receive commands from a user and convert them for submission tothe processor 1252. In addition, an external interface 1262 may providecommunication with the processor 1252, so as to enable near areacommunication of the mobile computing device 1250 with other devices.The external interface 1262 may provide, for example, for wiredcommunication in some implementations, or for wireless communication inother implementations, and multiple interfaces may also be used.

The memory 1264 stores information within the mobile computing device1250. The memory 1264 can be implemented as one or more of acomputer-readable medium or media, a volatile memory unit or units, or anon-volatile memory unit or units. An expansion memory 1274 may also beprovided and connected to the mobile computing device 1250 through anexpansion interface 1272, which may include, for example, a SIMM (SingleIn Line Memory Module) card interface. The expansion memory 1274 mayprovide extra storage space for the mobile computing device 1250, or mayalso store applications or other information for the mobile computingdevice 1250. Specifically, the expansion memory 1274 may includeinstructions to carry out or supplement the processes described above,and may include secure information also. Thus, for example, theexpansion memory 1274 may be provide as a security module for the mobilecomputing device 1250, and may be programmed with instructions thatpermit secure use of the mobile computing device 1250. In addition,secure applications may be provided via the SIMM cards, along withadditional information, such as placing identifying information on theSIMM card in a non-hackable manner.

The memory may include, for example, flash memory and/or NVRAM memory(non-volatile random access memory), as discussed below. The computerprogram product contains instructions that, when executed, perform oneor more methods, such as those described above. The computer programproduct can be a computer- or machine-readable medium, such as thememory 1264, the expansion memory 1274, or memory on the processor 1252.In some implementations, the computer program product can be received ina propagated signal, for example, over the transceiver 1268 or theexternal interface 1262.

The mobile computing device 1250 may communicate wirelessly through thecommunication interface 1266, which may include digital signalprocessing circuitry where necessary. The communication interface 1266may provide for communications under various modes or protocols, such asGSM voice calls (Global System for Mobile communications), SMS (ShortMessage Service), EMS (Enhanced Messaging Service), or MMS messaging(Multimedia Messaging Service), CDMA (code division multiple access),TDMA (time division multiple access), PDC (Personal Digital Cellular),WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS(General Packet Radio Service), among others. Such communication mayoccur, for example, through the transceiver 1268 using aradio-frequency. In addition, short-range communication may occur, suchas using a Bluetooth, WiFi, or other such transceiver (not shown). Inaddition, a GPS (Global Positioning System) receiver module 1270 mayprovide additional navigation- and location-related wireless data to themobile computing device 1250, which may be used as appropriate byapplications running on the mobile computing device 1250.

The mobile computing device 1250 may also communicate audibly using anaudio codec 1260, which may receive spoken information from a user andconvert it to usable digital information. The audio codec 1260 maylikewise generate audible sound for a user, such as through a speaker,e.g., in a handset of the mobile computing device 1250. Such sound mayinclude sound from voice telephone calls, may include recorded sound(e.g., voice messages, music files, etc.) and may also include soundgenerated by applications operating on the mobile computing device 1250.

The mobile computing device 1250 may be implemented in a number ofdifferent forms, as shown in the figure. For example, it may beimplemented as a cellular telephone 1280. It may also be implemented aspart of a smart-phone 1282, personal digital assistant, or other similarmobile device.

Various implementations of the systems and techniques described here canbe realized in digital electronic circuitry, integrated circuitry,specially designed ASICs (application specific integrated circuits),computer hardware, firmware, software, and/or combinations thereof.These various implementations can include implementation in one or morecomputer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms machine-readable medium andcomputer-readable medium refer to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including a machine-readablemedium that receives machine instructions as a machine-readable signal.The term machine-readable signal refers to any signal used to providemachine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniquesdescribed here can be implemented on a computer having a display device(e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor)for displaying information to the user and a keyboard and a pointingdevice (e.g., a mouse or a trackball) by which the user can provideinput to the computer. Other kinds of devices can be used to provide forinteraction with a user as well; for example, feedback provided to theuser can be any form of sensory feedback (e.g., visual feedback,auditory feedback, or tactile feedback); and input from the user can bereceived in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in acomputing system that includes a back end component (e.g., as a dataserver), or that includes a middleware component (e.g., an applicationserver), or that includes a front end component (e.g., a client computerhaving a graphical user interface or a Web browser through which a usercan interact with an implementation of the systems and techniquesdescribed here), or any combination of such back end, middleware, orfront end components. The components of the system can be interconnectedby any form or medium of digital data communication (e.g., acommunication network). Examples of communication networks include alocal area network (LAN), a wide area network (WAN), and the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

In situations in which the systems, methods, devices, and othertechniques here collect personal information (e.g., context data) aboutusers, or may make use of personal information, the users may beprovided with an opportunity to control whether programs or featurescollect user information (e.g., information about a user's socialnetwork, social actions or activities, profession, a user's preferences,or a user's current location), or to control whether and/or how toreceive content from the content server that may be more relevant to theuser. In addition, certain data may be treated in one or more waysbefore it is stored or used, so that personally identifiable informationis removed. For example, a user's identity may be treated so that nopersonally identifiable information can be determined for the user, or auser's geographic location may be generalized where location informationis obtained (such as to a city, ZIP code, or state level), so that aparticular location of a user cannot be determined. Thus, the user mayhave control over how information is collected about the user and usedby a content server.

Although various implementations have been described in detail above,other modifications are possible. In addition, the logic flows depictedin the figures do not require the particular order shown, or sequentialorder, to achieve desirable results. In addition, other steps may beprovided, or steps may be eliminated, from the described flows, andother components may be added to, or removed from, the describedsystems. Accordingly, other implementations are within the scope of thefollowing claims.

What is claimed is:
 1. A computer-implemented method, comprising:obtaining, by a system of one or more computers, a maternalelectrocardiogram (ECG) signal that represents an ECG of a pregnantmother during a first time interval, wherein the maternal ECG signal isacquired from one or more electrodes affixed to at least one of anabdominal region of the mother or a chest region of the mother;obtaining, by the system, a mixed maternal-fetal ECG signal thatrepresents a combined ECG of the mother and her fetus during the firsttime interval, wherein the mixed maternal-fetal ECG signal is acquiredfrom one or more electrodes of a vaginal probe located within a vaginalcanal of the mother; processing, by the system, the maternal ECG signaland the mixed maternal-fetal ECG signal to generate a fetal ECG signalthat represents the ECG of the fetus during the time interval, the fetalECG signal substantially excluding the maternal ECG signal; andproviding, by the system, an output based on the fetal ECG signal. 2.The computer-implemented method of claim 1, wherein the system comprisesa smartphone or a tablet computing device.
 3. The computer-implementedmethod of claim 1, further comprising synchronizing the maternal ECGsignal with the mixed maternal-fetal ECG signal.
 4. Thecomputer-implemented method of claim 1, wherein processing the maternalECG signal and the mixed maternal-fetal ECG signal to generate the fetalECG signal comprises subtracting the maternal ECG signal from the mixedmaternal-fetal ECG signal to generate the fetal ECG signal.
 5. Thecomputer-implemented method of claim 1, further comprising applying anadaptive filter to the maternal ECG signal before subtracting thematernal ECG signal from the mixed maternal-fetal ECG signal.
 6. Thecomputer-implemented method of claim 1, wherein the adaptive filtercomprises a Wiener filter.
 7. The computer-implemented method of claim1, wherein processing the maternal ECG signal and the mixedmaternal-fetal ECG signal to generate the fetal ECG signal comprisesusing a blind source separation technique to separate the fetal ECGsignal from the maternal ECG signal.
 8. The computer-implemented methodof claim 1, wherein processing the maternal ECG signal and the mixedmaternal-fetal ECG signal to generate the fetal ECG signal comprisesusing at least one of principal component analysis (PCA) or independentcomponent analysis (ICA) techniques.
 9. The computer-implemented methodof claim 1, further comprising analyzing the fetal ECG signal todetermine a distress level of the fetus; and wherein providing theoutput comprises generating an alert for presentation to a human user inresponse to a determination that the determined distress level of thefetus exceeds a threshold distress level.
 10. A computer-implementedmethod, comprising: receiving, by a system of one or more computers, afirst ECG signal, wherein the first ECG signal is a mixed maternal-fetalECG signal that represents a combined ECG of a pregnant mother and herfetus, wherein the mixed maternal-fetal ECG signal was acquired usingone or more electrodes from within a vaginal canal of the mother;processing, by the system, the first ECG signal to determine values forone or more features of the first ECG signal; determining, based on thedetermined values for the one or more features of the first ECG signal,a condition of at least one of the mother or the fetus; and providing,by the system, an output based on the determined condition of the atleast one of the mother or the fetus.
 11. The computer-implementedmethod of claim 10, wherein the features of the first ECG signalcomprise features of a waveform for a beat from the first ECG signal,the features of the waveform including a slope or an area of a portionof the waveform for the beat.
 12. The computer-implemented method ofclaim 10, wherein determining the condition of the at least one of themother or the fetus comprises accessing a model that correlates at leastone of maternal conditions or fetal conditions with ECG signal features.13. The computer-implemented method of claim 12, wherein the modelcomprises an artificial neural network.
 14. A vaginal probe for sensinginformation about a patient from within a vaginal canal of the patient,the probe comprising: a ring-shaped body structured and dimensioned forplacement within the vaginal canal of the patient; a set of ECG sensorscomprising one or more electrodes disposed on the ring-shaped body, theset of ECG sensors configured to abut walls of the vaginal canal whenthe ring-shaped body is placed within the vaginal canal of the patient,the set of ECG sensors configured to detect a maternal ECG signal if thepatient is not pregnant or to detect a mixed maternal-fetal ECG signalif the patient is pregnant in at least the second or third trimesters; awireless communications interface configured to wirelessly transmit RFsignals that encode information about the maternal ECG signal or themixed maternal-fetal ECG signal; and a controller configured to activateor deactivate ECG signal acquisition and transmission.
 15. The vaginalprobe of claim 14, further comprising at least one of a temperaturesensor, a pH sensor, an accelerometer, a gyroscope, electromyography(EMG) sensors, or electrochemical sensors.
 16. The vaginal probe ofclaim 14, wherein the ring-shaped body is made of a nitinol alloy. 17.The vaginal probe of claim 14, further comprising an induction coil thatis configured to energize the vaginal probe when an external inductivepower source is brought into proximity of the induction coil of thevaginal probe.